- Laxenburg, Niederösterreich, Austria
brian fath
Towson University, Biological Sciences, Faculty Member
Research Interests: Mathematics, Ecosystems Ecology, Community Ecology, Network Analysis, Ecological Networks, and 22 moreSocial Network Analysis (SNA), Food web ecology, Theoretical biology, Systems Ecology, Biological Sciences, Complex System, Mathematical Sciences, Food web, Animals, Modularity, Eigenvalues, Hierarchy, Functional integration, Ecosystem, Large Scale Structure, Eigenvalue Problems, Small World, Network Model, SPECTRAL RADIUS, Food Chain, Quantitative Method, and Similarity Function
Research Interests:
Large-scale structural patterns commonly occur in network models of complex systems including a skewed node degree distribution and small-world topology. These patterns suggest common organizational constraints and similar functional... more
Large-scale structural patterns commonly occur in network models of complex systems including a skewed node degree distribution and small-world topology. These patterns suggest common organizational constraints and similar functional consequences. Here, we investigate a structural pattern termed pathway proliferation. Previous research enumerating pathways that link species determined that as pathway length increases, the number of pathways tends to increase without bound. We hypothesize that this pathway proliferation influences the flow of energy, matter, and information in ecosystems. In this paper, we clarify the pathway proliferation concept, introduce a measure of the node--node proliferation rate, describe factors influencing the rate, and characterize it in 17 large empirical food-webs. During this investigation, we uncovered a modular organization within these systems. Over half of the food-webs were composed of one or more subgroups that were strongly connected internally, but weakly connected to the rest of the system. Further, these modules had distinct proliferation rates. We conclude that pathway proliferation in ecological networks reveals subgroups of species that will be functionally integrated through cyclic indirect effects.
Research Interests: Mathematics, Ecosystems Ecology, Community Ecology, Network Analysis, Ecological Networks, and 22 moreSocial Network Analysis (SNA), Food web ecology, Theoretical biology, Systems Ecology, Biological Sciences, Complex System, Mathematical Sciences, Food web, Animals, Modularity, Eigenvalues, Hierarchy, Functional integration, Ecosystem, Large Scale Structure, Eigenvalue Problems, Small World, Network Model, SPECTRAL RADIUS, Food Chain, Quantitative Method, and Similarity Function
Research Interests:
Research Interests:
Research Interests:
While there is tremendous interest in sustainability, a fundamental theory of sustainability does not exist. We present our efforts at constructing a theory from Information Theory and Ecological Models. We discuss the state of complex... more
While there is tremendous interest in sustainability, a fundamental theory of sustainability does not exist. We present our efforts at constructing a theory from Information Theory and Ecological Models. We discuss the state of complex systems that incorporate ecological and other components in terms of dynamic behavior in a phase space defined by the system state variables. From sampling the system trajectory, a distribution function for the probability of observing the system in a given state is constructed, and an expression for the Fisher information is derived. Fisher information is the maximum amount of information available from a set of observations, in this case, states of the system. Fisher information is a function of the variability of the observations such that low variability leads to high Fisher information and high variability leads to low Fisher information. Systems in stable dynamic states have constant Fisher information. Systems losing organization migrate toward higher variability and lose Fisher information. Self-organizing systems decrease their variability and acquire Fisher information. These considerations lead us to propose a sustainability hypothesis: “sustainable systems do not lose or gain Fisher information over time.” We illustrate these concepts using simulated ecological systems in stable and unstable states, and we discuss the underlying dynamics.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests: Ecological Economics, Modeling, Evaluation, Economic Development, Environmental Monitoring, and 14 morePublic Health, Ecosystem health, Multidisciplinary, Cities, Urban Renewal, Case Study, Conceptual Model, Health Status, Human health, Mathematical Model, Environmental quality, Ecosystem, Human Perception, and Urban Ecosystem
Research Interests:
Research Interests:
This article introduces and summarizes the foundations of network environ analysis and describes four primary properties resulting from this research. These properties—dominance of indirect effects (Higashi and Patten 1986), network... more
This article introduces and summarizes the foundations of network environ analysis and describes four primary properties resulting from this research. These properties—dominance of indirect effects (Higashi and Patten 1986), network amplification (Patten and others 1990), network homogenization (Patten and others 1990), and network synergism (Patten 1991)—provide insight into the behavior of holistic network interactions. In short, amplification, homogenization, and indirect effects demonstrate the influence of the indirect flows in a system to show that energy or matter cycling allows flow to return to the same component many times and tend to become evenly distributed within the network. Synergism relates direct and indirect, qualitative relations to show that network organization is, on the whole, more mutualistic than is apparent from direct interactions alone. Using network analysis, objects can be studied as part of a connected system and the indirect effects can be identified and quantified. This is a fundamentally different way of investigating ecosystems, and it gives a quantitative foundation to the widely held perception of the interconnectedness of nature.